Abstract One of the major challenges in Civil Engineering is the gradual search for more viable and efficient solutions to improve structural performance. In this case, Structural Engineering has been encouraged to create and develop materials and methods that allow for the production of more slender structures that are at the same time safe and economical. One of these solutions is structural optimization. This article addresses topological optimization in three-dimensional problems considering volume minimization based on a stress criterion. The method used is Evolutionary Structural Optimization (ESO) with the aid of the structural analysis software Salome-Meca®, via the Finite Element Method (FEM). For this, an algorithm in Python® programming language is implemented to be the input file of the free numerical analysis software Code-Aster® solver of Salome-Meca®. In the ESO process, underutilized elements of the structural system are removed, that is, elements whose stress have values lower than the maximum limit stress of the structure. This optimization is performed using a combination of two isotropic materials, with the aim of studying the influence of different constitutive models on the optimal topologies of the proposed problems, analyzing the topological structural behavior, as well as investigating how the mechanical and physical properties impact the final topology. Finally, based on the considerations and research in question, the optimization of composite structures is interesting because it obtains a more efficient structure that takes advantage of the positive complementary characteristics of two materials working together.
Abstract This article presents the results of a mineral prospecting study of active stream sediment and alluvial sediment from the Araguari River, Minas Gerais, Brazil. Sediment samples were collected from the river's source to the Desemboque district, where, between the years 1743 and 1781, 1,500 kg of alluvial gold were extracted. Therefore, this study analyzed samples of alluvial sediments and active watercourses to identify potential mineralization zones in a region historically associated with gold deposits. Geochemical assays indicate Pt concentrations exceeding Clarke values, contrasting with relatively low gold (Au) levels. Correlations between Cu and Ag, as well as rare earth elements (Ce and La), suggest complex mineralization processes linked to regional lithology and hydrothermal activity. These findings expand the understanding of the Araguari basin’s metallogenic potential and highlight opportunities for future exploration targeting platinum group elements and associated metals.
Abstract The key-block theory enables the identification of stable and unstable blocks along the perimeter of underground excavations in hard rock. Monte Carlo simulation can be used to develop a probabilistic extension of the key-block theory. This article aims to examine the suitability of the reliability index as an interpretive tool for assessing block stability in analyses where variability is explicitly represented. A Monte Carlo simulator was implemented using the vector formulation of the key-block theory. In the simulations, variability in joint orientations is modeled with a spherical distribution, while strength variability is represented by a normal distribution. A first study showed that a lognormal model more appropriately represents the probabilistic distribution of the safety factor for the wall blocks in the studied case. This is due to the highly truncated probability density function of the Fischer distribution adopted for the orientation of the planes. A second study found that significant changes in block failure modes occur only under a large dispersion of joint orientations. A third study indicated that, for a roof block failing under self-weight, the required reinforcement level can be determined by verifying the consistency of the reliability index with international code criteria. The implemented simulator was validated through comparison with a commercial simulator. The developed tool offers advantages over the commercial reference, such as the direct calculation of the reliability index and the identification of the change in the failure mechanism that occurs for wide orientation dispersion.
Abstract The equivalent frame method is widely used for the structural analysis of masonry buildings subjected to lateral loads. In this approach, masonry structural components are idealized as macro-elements, which consist of reticulated finite elements formulated to simulate the quasi-brittle behavior of masonry and its typical failure mechanisms. This study investigates a macro-element with a mixed force-based formulation applied to the modeling of structural masonry shear walls. The study is based on a previously developed macro-element for unreinforced masonry panels, using the Timoshenko beam theory, which adopts a uniaxial constitutive model for masonry and incorporates a non-linear shear hinge. The cross-sectional stiffness matrix is obtained through analytical integration, without fiber discretization. This macro-element is capable of reproducing the failure mechanisms of rocking, bed joint sliding, and diagonal cracking. The present study focuses on the enhancement of the macro-element through extensions to the original formulation and modifications to the non-linear solution procedure. The main contributions include the introduction of a tensile branch into the masonry constitutive law, as well as the incorporation of reinforcement through a fiber-based approach. In addition, modifications were introduced in the matrix representation of the cross-section force-deformation relationship, resulting in a more robust numerical scheme with improved convergence. The macro-element was applied to the numerical simulation of experimentally tested unreinforced and reinforced masonry shear walls, yielding results consistent with data reported in literature.
Abstract The load transfer methods are important tools for predicting the behavior of the load-displacement curve for piles. Several studies indicate that these curves in single piles can be well represented by hyperbolic functions. In this context, this research aims to predict the load transfer curves in single piles using hyperbolic functions based on easily obtainable parameters and measurements. For this purpose, data from 48 instrumented single piles (driven and bored), executed in granular soil profiles and subjected to static load tests were collected, obtaining the parameters of hyperbolic curves that define the t-z and q-z load transfer curves. Correlations of the parameters of the hyperbolic curves with measurements from cone penetration tests (CPT) or standard penetration tests (SPT), pile geometry, initial geostatic stresses, and deformation parameters of the load transfer curves were performed. Validation indicated results converging to the proposed predictions, and in general, predictions based on CPT measurements, and using deformation parameters Ms and Mb showed more convergent results.
Abstract The continuous advancement in new materials and manufacturing processes enables innovative applications to emerge daily in the oil and gas sector. Among these, concrete extrusion technology, enhanced by plasticizer addition and reduced porosity, offers improved mechanical properties compared to conventional cementitious components. This article evaluates the technical feasibility of replacing high-alloy steel pipes with extruded concrete pipes for oil well casing. Using finite element analysis developed in Ansys®, four critical scenarios were evaluated: (i) radial tensile stresses associated with gas bubbles, ii) radial compressive stresses linked to pore pressure and formation fracturing, iii) axial tensile stresses due to string movement, and iv) axial tensile stresses related to casing string unlocking. Results indicate that extruded concrete pipes can safely withstand differential radial pressures of up to 1,000 psi, provided a minimum wall thickness of 100 mm is adopted. However, axial load simulations revealed critical limitations: maximum tensile stresses reached 96.6 MPa during lifting operations and 193.1 MPa during unlocking, both far exceeding the material’s tensile strength of 30 MPa. These findings demonstrate that, despite the material’s adequate performance under radial loading, extruded concrete pipes are unsuitable for axial loading conditions inherent to casing operations. Further research is recommended on hybrid or fiber-reinforced alternatives to enhance tensile resistance and extend the potential of concrete extrusion to downhole applications.
Abstract Hydrogen sulfide (H2S) emissions from mining tailings dams pose persistent environmental and operational challenges due to their corrosiveness, toxicity, and intense odor. In a Brazilian mining complex, sulfate-reducing bacteria (SRB) associated with unoxidized ore and recirculated process water were identified as the primary source of H2S. Initial mitigation using a glutaraldehyde-based biocide temporarily suppressed microbial activity but proved unsustainable due to high dosing costs and the development of microbial resistance. Subsequently, sodium hypochlorite (NaClO) was tested as an oxidizing agent to chemically neutralize H2S before degassing. Laboratory and industrial-scale trials confirmed that NaClO, at an optimized dosage of 10 L/h, effectively eliminated odors within 10-20 minutes, with no reappearance over a 48-hour observation period and reducing odor complaints to zero, without compromising the process performance. This approach also reduced operational costs by 90% compared to the biocide. This case study highlights the benefits of integrating microbiological diagnostics with adaptive chemical strategies to establish a scalable, cost-effective solution for odor control in mining environments.
Abstract The Last Planner System (LPS) is a collaborative production planning and control approach in lean construction that improves workflow reliability by converting work into reliable commitments and systematically learning from plan failures. Despite its demonstrated benefits internationally, LPS adoption in Sri Lanka remains limited and often partial, largely due to insufficient organizational and industry-level capacities. This study identifies the capacity requirements for full LPS implementation in the Sri Lankan construction industry and proposes practical capacity-building strategies to address them. Nine expert interviews were conducted using qualitative design and analyzed using qualitative content analysis in NVivo. Nineteen capacity requirements were identified across LPS planning horizons. They were classified as internal (e.g., lean/LPS knowledge, structured training, leadership and change management, communication practices and media, top-management support, and adequate human/technical resources) and external (e.g., client approval processes, external stakeholder support, industrial training capability, lean information infrastructure, and supportive legal and regulatory frameworks). Twenty-five strategies were developed to strengthen these capacities, emphasizing phase-based LPS training and coaching, leadership development, collaborative contract and procurement arrangements, and institutional support mechanisms (e.g., CPD programs and lean information portals). The resulting strategic framework provides an actionable roadmap for contractors, clients, and regulators to enable sustainable LPS deployment in Sri Lanka.
Abstract Depending on the fuel and process conditions, nitrogen oxides (NOx) are important air pollutants generated by combustion processes when using ambient air (which contains N2) or nitrogen-containing fuels. The iron and steel industry, particularly iron ore pelletization, is a significant NOx emitter. Although NOx abatement has been widely applied in various industries, the straight grate pelletization process remains under-researched despite its global relevance. This study systematically reviews the technical publications on NOx reduction techniques applicable to iron ore pelletization, aiming to identify practical and scalable solutions for industrial implementation. Using 19 Boolean search queries across two major academic databases, we retrieved 626 articles, ultimately selecting 56 for in-depth analysis.The acquired data revealed that coal (39.29%) was the most used fuel, while natural gas (1.79%), a cleaner alternative, was rarely utilized. Selective Non-Catalytic Reduction (SNCR) emerged more often (21.43%) than Selective Catalytic Reduction (SCR), and ammonia was the predominant reducing agent (68.42%). Strategies, such as reducing peak combustion temperature (48.21%), also appeared regularly. Regionally, China (33.33%), the United Kingdom (16.67%), and South Korea (12.50%) led research output. These findings emphasize the significant gaps-especially the lack of focus on natural gas and the straight grate pelletization process-while highlighting to promising avenues for innovation. By consolidating current knowledge and practices, this review provides a foundation for future research and industrial strategies aimed at achieving cleaner, more sustainable iron ore pelletization technologies.
Abstract In recent years, military conflicts between major phosphorus suppliers have disrupted the global fertilizer distribution chain. This scenario highlights the critical need for precise density measurements in phosphate mining to improve reserve estimation and reconciliation. In Brazil, formation density is traditionally estimated from drill cores, using hydrostatic balance methods, which can be time-consuming and less reliable for poorly consolidated rocks. Gamma-gamma geophysical logging emerges as a more effective alternative, offering high-resolution density data with rapid acquisition. The use of these nuclear tools requires some special care, such as data acquisition from the inside of boreholes with steel casing, essential for operational safety. However, this procedure introduces measurement changes in the density log readings. This study aimed to comprehend the main factors involved in these gamma-gamma readings through direct comparisons between logging records made in holes with and without casing. In this way, it was possible to suggest a workflow to correct density readings when influenced by the presence of steel casing. Data from four boreholes drilled in the Tapira Mining Complex, Minas Gerais (Brazil) were used. The correction creates synthetic density records that present good correspondence with measurements from uncased boreholes while being supported by borehole diameter control from caliper records. Finally, the results show that gamma-gamma density logging, applied to cased holes, can be a reliable and efficient method for density measurement in phosphate deposits, especially in friable ore zones.
Abstract Geotechnical properties vary spatially owing to their mineralogical composition, stress history, and deposition processes, even within homogeneous soil layers. This high degree of variability imposes considerable limitations on the calculation and simulation of models based on deterministic parameters extracted from the field. Mine tailings exemplify this scenario, where the difficulty of sample extraction and laboratory characterization further complicates the challenges. Consequently, field investigation becomes a crucial factor in determining the behavior to be used in geomechanical models. To address this issue, this study focuses on quantifying statistical parameters, including the mean, standard deviation, probability density function, and fluctuation scale-scarce in the literature-derived from direct measurements of piezocone tests and related strength parameters. The results indicate that despite the high variability of the deposit, after a careful profile evaluation considering the characteristic behavior of coarse and fine materials, it was feasible to evaluate the adherence of both normal and lognormal distributions for strength parameters. The fluctuation scales also show high dispersion, ranging from 0.1 to 3.3 meters. This research contributes to a comprehensive understanding of the spatial variability in mine tailings and provides practical insights for future applications.
Abstract This article presents a numerical analysis of large deflections (elastica) in prismatic and non-prismatic cantilever beams and columns subjected to either concentrated or uniformly distributed loads, accounting for axial deformation. A mathematical model is derived, consisting of three coupled differential equations that govern the position of the member in its deformed configuration. The nonlinear boundary value problem is solved using an accurate numerical procedure based on the Dormand-Prince Runge-Kutta method, combined with the shooting method. Highly accurate tabulated results are presented for various taper ratios (ranging from 0.2 to 1.0) of a rectangular cross-section with linearly varying height, including free-end positions, buckling loads, and post-buckling behavior. Differences in the responses are observed when axial deformation is neglected, particularly in members with predominantly axial loading, varying according to the taper ratio. When axial deformation is neglected, the results show good agreement with available analytical and numerical solutions, demonstrating the accuracy of the proposed approach.
Abstract This study investigated how technological advancement in the geotechnical field contributes to ensuring safety in idle mine pits. A qualitative research approach was used to analyze relevant literature on geotechnical safety in the continuous monitoring of idle mine pits. The study highlighted the importance of combining geotechnical principles-such as slope stability analysis and the behavior of soils and rocks-with advanced monitoring technologies, including inclinometers, piezometers, extensometers, water level indicators, topographic prisms, drones, and remote sensing. It also emphasized the implementation of risk management strategies and early warning systems to provide real-time information and allow for quick responses to signs of instability. The continuous training of professionals and effective communication between all stakeholders are crucial for the effectiveness of safety strategies. We concluded that the integrated application of these practices is essential to ensure the stability of mine pits, protect nearby communities, and mitigate geotechnical risks.
Abstract AISI 52100 steel is an alloy steel with a high carbon and chromium content, widely used in industry to produce bearings. Through high energy ball milling, it is possible to obtain powders in submicrometer scale for later use in a new product using powder metallurgy. In this study, powders of AISI 52100 steel with a 3% alumina addition were obtained from scraps of this steel, through high energy ball milling. Parameters of speed (200, 300 and 400 rpm), ball to powder ratio (10:1, 15:1 and 20:1) and time (10, 20 and 30 hours) were varied to determine the best milling condition for the AISI 52100 steel with alumina. Particle size analysis through scanning electron microscopy was used to identify the ideal parameters of time, milling speed and ball to powder ratio. The results obtained indicated that the ball to powder ratio was the parameter that most affected the particle size.
Abstract The pumping of iron ore slurry through long-distance pipelines requires reliable prediction of energy losses to ensure operational efficiency and maintenance planning. This study develops a predictive model for energy loss by integrating real operational data with statistical validation. Operational data, including slurry properties and flow parameters, were collected over seven months and used to develop a linear regression model, which identified flow rate as the most critical variable, with a Pearson correlation coefficient of 0.735. The model was validated using 12 months of field data from 2022, confirming its ability to detect trends of increasing pressure drop and to anticipate pig-cleaning operations. The application of this monitoring method led to a statistically significant increase in the average flow rate of 11.98 m3/h after pigging campaigns. This operational improvement resulted in an estimated production gain of 13,299 dry metric tons per month. Although the resulting equation is specific to Samarco’s Pipeline 2, the methodology offers a practical and replicable framework for transforming historical data into a proactive tool for maintenance and operational optimization in other slurry pipelines, enhancing efficiency and supporting predictive decision-making.
Abstract Predicting the pile’s bearing capacity still represents a significant challenge in Geotechnical Engineering, since it requires the knowledge of soil parameters and the soil-pile interaction mechanism during and after foundation execution. This study developed a model based on multilayer perceptron Artificial Neural Networks (ANN) with the Levenberg-Marquardt training algorithm to predict the bearing capacity of driven and bored piles. For this purpose, results from Standard Penetration Tests (SPT) and static load tests performed on 343 piles were compiled. The input variables adopted for the model were: pile diameter and length, penetration resistance (NSPT), and soil type. Different models were then trained and validated with the aid of MATLAB® software. Comparison of the results obtained allowed the selection of the best-performing neural model. The coefficient of determination (R2) and the root mean square error (RMSE) in the validation phase were 0.96 and 0.02, respectively. These values were satisfactory, given the phenomenon’s complexity. The case study, which sought to analyze the generalization capacity and applicability of the neural model, showed that the model presented a better performance than the semi-empirical methods of Aoki-Velloso (1975) and Décourt-Quaresma (1978). These results suggest that the multilayer perceptron ANN is a promising tool for predicting the bearing capacity of piles. This work contributes by providing a neural model trained with a comprehensive dataset representative of diverse soil conditions in Brazil, covering both driven and bored piles, and by making its parameters available for practical application in geotechnical design, a step often overlooked in previous studies.
Abstract In Brazil, many cities have challenges in managing road infrastructure. Pavement management is an important aspect of municipal public administration, since it guides strategic planning, organizes processes, and sets goals to optimize available resources for ensuring service quality and city dynamics. However, there is a lack of studies focusing on the context of large cities. This study aimed to fill this gap by proposing a model for urban pavement management in large cities, using Belo Horizonte, in Minas Gerais, Brazil, as a case study. Based on the history of pavement maintenance between 2009 and 2021, the methodology characterized the municipal road network and maintenance actions practiced, enabling a comprehensive analysis of the maintenance diagnosis, planning, and operationalization steps. The results showed the life cycle of pavements based on their functional evaluation and respective road classification. Guidelines were presented for maintenance and rehabilitation strategies for each stage of deterioration.
Abstract Recent research has increasingly focused on the inelastic behavior of steel frames under severe dynamic forces, which can lead to plastic deformation, damage accumulation, and potential collapse. In such conditions, structures must dissipate significant energy - a property facilitated by steel’s ductility, enabling large deformations and force redistribution beyond yield limits. This study evaluates the nonlinear dynamic response of planar steel frames, particularly highlighting the role of steel-yielding in inducing hysteretic damping. The analysis employs an elastoplastic material model with plasticity monitored using the refined plastic-hinge method (RPHM). The model incorporates residual stresses, cross-sectional plastic resistance, and second-order effects from large displacements and rotations. The numerical approach integrates the finite element method (FEM) with the Newmark scheme and Newton-Raphson iterations, providing insights into material nonlinearity, energy dissipation, and structural stability under dynamic excitation. Numerical simulations of two steel frames clearly illustrate the influence of hysteretic damping caused by material yielding, demonstrating its critical impact on dynamic structural response.
